Indoor SLAM Using Movement Data to Resolve Obstacle Ambiguity
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Solution Overview
Problem
Current indoor localization methods, such as beacon-based systems and SLAM, face challenges in precision and complexity, especially in environments without external GPS signals and require expensive infrastructure, while simultaneously mapping indoor environments remains inefficient.
Innovation Solution
A method for simultaneous localization and mapping that generates a map and determines object movement using data captured by the object, employing a polling signal to detect obstacles, filter responses, and weight probabilities based on movement information, allowing for precise mapping without complex infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If beacon-based localization systems are deployed to achieve precise indoor positioning, then localization precision is improved, but device complexity and infrastructure cost increase
Solution Approach 1:
The object localizes itself by transmitting polling signals and processing its own received signals to determine position and generate maps, eliminating the need for external beacon infrastructure. The object serves its own localization needs through self-contained sensing and processing capabilities.
Solution Approach 2:
The patent extracts the localization function from the environment (beacons) and places it entirely on the moving object. The object carries all necessary sensing and processing equipment to perform localization independently, removing the infrastructure burden.
2Adaptability or versatility
If SLAM methods are used to simultaneously localize and map the environment, then mapping capability is improved, but computational complexity and data processing requirements increase
Solution Approach 1:
The patent performs preliminary actions by having the object transmit polling signals continuously to pre-collect signal propagation data from multiple directions. This preliminary data collection simplifies subsequent localization and mapping computations by having measurement data already available.
Solution Approach 2:
The object periodically transmits polling signals at regular intervals to continuously update its position and environment map. This periodic measurement approach provides steady data flow for incremental map building and position updates without requiring complex batch processing.
3Measurement precision
If time of arrival localization is used with synchronized signals, then localization precision is improved, but system synchronization requirements and infrastructure complexity increase
Solution Approach 1:
Instead of having beacons transmit synchronized signals to the object, the patent inverts the approach by having the object transmit polling signals to beacons. The object then measures the time of arrival of reflected signals, eliminating the need for complex synchronization between multiple transmitters.
Solution Approach 2:
The patent uses reflected signals from the environment as an intermediary to perform localization. The object transmits signals that reflect off environmental features and return to the object, using the environment itself as the measurement intermediary rather than requiring direct beacon-to-object signal paths.
4Area of stationary object
If extensive beacon networks are deployed to cover large indoor areas, then coverage area is improved, but cost and installation complexity increase
Solution Approach 1:
The moving object performs its own environmental scanning and mapping by transmitting polling signals in multiple directions and processing the reflected signals. This self-contained approach allows the object to operate in any covered area without requiring pre-deployed beacon infrastructure.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method provides precise and efficient simultaneous localization and mapping of objects in indoor environments, resolving ambiguity and improving mapping accuracy by integrating movement information into the mapping process, reducing the need for extensive infrastructure and enhancing navigation capabilities.
Implementation Method 1
transmitting a polling signal and receiving a response signal resulting from the transmission of the polling signal
Data Source
AI summary
A method for simultaneous localization and mapping of an object in an indoor environment, including autonomous location and mapping. The method includes generating a map of the indoor environment and determining movement of the object on the basis of data captured by the object, the localization and mapping method jointly generating the map and determining the movement. Ambiguity between two positions of an obstacle on a map during generation is thus resolved by taking into account the movement of the object generating the map, without the need for complex implementation elements.